新增涨停处理和自定义个股权重 (#1)
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20c1477b42
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trader.py
65
trader.py
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@ -23,14 +23,18 @@ class Trader(Account):
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ascending (bool): 因子方向
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with_st (bool): 是否包含st
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tick (bool): 是否开始tick模拟模式(开发中)
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weight (str): 权重分配
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- avg: 平均分配，每天早盘重新分配，日中交易不重新分配
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weight ([str, pd.DataFrame]): 权重分配
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- avg (str): 平均分配，每天早盘重新分配，日中交易不重新分配
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- (pd.DataFrame): 自定义股票权重，包含每天个股指定的权重，会自动归一化
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amt_filter (set): 20日均成交额筛选，第一个参数是筛选下限，第二个参数是筛选上限，可以只提供下限
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data_root (dict): 对应各个目标因子的交易价格数据，必须包含stock_code和price列
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ipo_days (int): 筛选上市时间
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slippage (tuple): 买入和卖出滑点
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commission (float): 佣金
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tax (dict): 印花税
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exclude_list (list): 额外的剔除列表，会优先满足该剔除列表中的条件，之后再进行正常的调仓
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- abnormal: 异常公告剔除，包含中止上市、立案调查、警示函等异常情况的剔除
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- report: 财报同比下降50%以上剔除
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"""
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def __init__(self,
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signal: Dict[str, pd.DataFrame]=None,
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@ -62,9 +66,9 @@ class Trader(Account):
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self.signal[s] = gft.return_factor(self.signal[s], self.signal[s].index.min(), self.signal[s].index.max(), return_type='origin')
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else:
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raise ValueError('type of signal is invalid')
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# ----------
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# --------------------
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# 参数检验
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# ----------
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# --------------------
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# interval
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self.interval = []
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for s in signal:
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@ -93,12 +97,17 @@ class Trader(Account):
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if isinstance(ascending, bool):
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self.ascending = ascending
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else:
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raise ValueError('invalid type for ascending')
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raise ValueError('invalid type for `ascending`')
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# with_st
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if isinstance(with_st, bool):
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self.with_st = with_st
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else:
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raise ValueError('invalid type for with_st')
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raise ValueError('invalid type for `with_st`')
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# weight
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if isinstance(weight, (str, pd.DataFrame)):
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self.weight = weight
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else:
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raise ValueError('invalid type for `weight`')
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# amt_filter
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if isinstance(amt_filter, (set,list,tuple)):
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if len(amt_filter) == 1:
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@ -173,7 +182,23 @@ class Trader(Account):
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pass
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else:
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self.today_data['close'] = DataLoader(self.today_data['basic'].data[['close_post']].rename(columns={'close_post':'price'}))
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def get_weight(self, date, total_weight, next_position):
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"""
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计算个股仓位
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"""
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if isinstance(self.weight, str):
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if self.weight == 'avg':
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return total_weight / len(next_position)
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if isinstance(self.weight, pd.DataFrame):
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date_weight = self.weight.loc[date].dropna().sort_index()
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try:
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weight_list = date_weight.loc[next_position['stock_code'].to_list()].values
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weight_list = total_weight * weight_list / sum(weight_list)
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return weight_list
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except:
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raise ValueError(f'not found stock weight in {date}')
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def get_next_position(self, date, factor):
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"""
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计算下一时刻持仓
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@ -182,10 +207,15 @@ class Trader(Account):
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if len(self.position) > 0:
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last_position = self.position['stock_code'].values
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last_position = factor.loc[last_position].sort_values(ascending=self.ascending)
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max_trade_num = max(int(self.interval.loc[date]*self.num), self.num-len(self.position))
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if len(self.position) <= self.num:
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# 如果昨日持仓本身就不足持仓数量则不用足额换仓
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max_sell_num = min(int(self.interval.loc[date]*self.num), int(self.interval.loc[date]*self.num)+len(self.position)-self.num)
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else:
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# 如果昨日持仓本身就超额持仓数量则超额换仓
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max_sell_num = max(int(self.interval.loc[date]*self.num), int(self.interval.loc[date]*self.num)+len(self.position)-self.num)
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else:
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last_position = pd.Series()
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max_trade_num = self.num
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max_sell_num = self.num
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target_list = []
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# 获取用于筛选的数据
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stock_status = self.today_data['basic'].get(factor.index.values, 'opening_info').sort_index()
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@ -198,6 +228,8 @@ class Trader(Account):
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stock_ipo_filter = stock_ipo_days.copy()
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stock_ipo_filter.loc[:] = 0
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stock_ipo_filter.loc[stock_ipo_days > self.ipo_days] = 1
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# 剔除列表
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# 交易列表
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if self.leverage <= 1.0:
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# 获取当前时间目标列表和冻结(无法交易)列表:
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@ -249,23 +281,28 @@ class Trader(Account):
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continue
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else:
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sell_list.append(stock)
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if len(sell_list) >= max_trade_num:
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if len(sell_list) >= max_sell_num:
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break
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# ----- 买入 -----
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# 卖出后持仓列表
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after_sell_list = set(last_position.index) - set(sell_list)
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max_trade_num = min(max_trade_num, self.num-len(last_position)+len(sell_list))
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cant_buy_list = [] # 涨停股记录
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max_buy_num = max(0, self.num-len(last_position)+len(sell_list))
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for stock in target_list:
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if stock in after_sell_list:
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continue
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else:
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if stock_status.loc[stock] in [4,6]:
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cant_buy_list.append(stock)
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buy_list.append(stock)
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if len(buy_list) == max_trade_num:
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if len(buy_list) == max_buy_num:
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break
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next_position = pd.DataFrame({'stock_code': list((set(last_position.index) - set(sell_list)) | set(buy_list))})
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next_position['date'] = date
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next_position['weight'] = self.leverage / len(next_position)
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next_position['weight'] = self.get_weight(date, self.leverage, next_position)
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# 剔除无法买入的涨停股，这部分仓位空出
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next_position = next_position[~next_position['stock_code'].isin(cant_buy_list)]
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next_position['margin_trade'] = 0
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else:
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# 如果有杠杆
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@ -375,7 +412,7 @@ class Trader(Account):
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next_position['date'] = date
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# 融资融券数量
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margin_num = len(next_margin_list)
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next_position['weight'] = (1 + (margin_num / self.num)) / self.num
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next_position['weight'] = self.get_weight(date, 1 + (margin_num / self.num), next_position)
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next_position['margin_trade'] = 0
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next_position = next_position.set_index(['stock_code'])
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next_position.loc[next_margin_list, 'margin_trade'] = 1
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